Bipolar DisordersNeurosciencePeer-reviewed journal article
Identifying mood instability and circadian rest-activity patterns using digital remote monitoring and actigraphy in participants at risk for bipolar disorder
Priyanka PanchaliD, Natalie NelisseniD, Niall M. McGowaniD, Lauren Z. AtkinsoniD, Kate E. A. SaundersiD, Paul J. HarrisoniD, Matthew F. S. RushworthiD, Dejan DraschkowiD, John Richard GeddesiD, Anna Christina NobreiD, Catherine J. HarmeriD
Abstract
Mood instability and circadian rhythm disruptions are both of increasing interest with regard to a number of psychiatric disorders, notably bipolar disorder (BD), but understanding of their nature and their interrelationship are incomplete. By definition, both have an integral temporal component and, as such, measuring them longitudinally and remotely is desirable. We conducted the Cognition and Mood Evolution across Time (COMET) study to assess the feasibility and value of digital devices to capture mood, its instability, and daily rest-activity patterns, over a 10-week period, in two groups of participants. The first group (n=37) were selected as scoring >7 on the Mood Disorder Questionnaire (MDQ) ( high MDQ), thereby having a history of mood elevation and being at risk for BD. They were compared with a group (n=37) scoring <5 on the MDQ ( low MDQ). Over a 10-week period, using a tablet, mood was rated daily, clinical ratings of depression, mania, and anxiety were captured weekly via the True Colours app, and a GENEactiv actigraph was worn to capture rest-activity pattern data. The main findings are that (1) MDQ score predicts mood instability; (2) high MDQ score is associated with more negative affect and mood symptoms than people with low MDQ, and with a different circadian activity profile; and (3) mood instability and circadian indices appear uncorrelated. The implications are that (1) remote monitoring of these domains is feasible and valuable; (2) selection of participants based on MDQ score is useful for studying mood (in)stability; and (3) the approach has potential for studies of clinical populations and for experimental medicine studies assessing interventions to reduce mood instability.
- Citations
- 1
- FWCI
- 0.00
- Field percentile
- 0th percentile
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Longitudinal Stability of Mood-Related Resting-State Networks in Youth with Symptomatic Bipolar-I/II Disorder
Danella Hafeman, Jamie A. Feldman, … Boris B. Birmaher·Translational PsychiatryPeer-reviewed·Jun 3, 2025
- Longitudinal hair cortisol in bipolar disorder and a mechanism based on HPA dynamics
Tomer Milo, Lior Maimon, … Uri Alon·iSciencePeer-reviewed·Feb 15, 2024
- Applying machine learning in motor activity time series of depressed bipolar and unipolar patients.
Petter Jakobsen, Enrique Garcia-Ceja, … Ketil Joachim Oedegaard·PLoS ONEPeer-reviewed·Aug 24, 2020
- Misperceiving momentum: computational mechanisms of biased striatal reward prediction errors in bipolar disorder
Hestia Moningka, Wael El‐Deredy, … Liam Mason·Biological Psychiatry Global Open SciencePeer-reviewed·Apr 30, 2024
- Genome-wide association study of circadian rhythmicity in 71 500 UK Biobank participants and polygenic association with mood instability
Amy Ferguson, Laura M. Lyall, … Daniel J. Smıth·EBioMedicinePeer-reviewed·Aug 14, 2018
- Unpredictable circadian rhythm disruption in Wistar rats: biological and behavioural changes reflecting bipolar disorder pathophysiology
Heather K. Macpherson, Roger B. Varela, … Susannah J. Tye·bioRxiv·Sep 6, 2025